TY - JOUR
T1 - How artificiality and intelligence affect voice assistant evaluations
AU - Guha, Abhijit
AU - Bressgott, Timna
AU - Grewal, Dhruv
AU - Mahr, Dominik
AU - Wetzels, Martin
AU - Schweiger, Elisa
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022
Y1 - 2022
N2 - Widespread, and growing, use of artificial intelligence (AI)–enabled voice assistants (VAs) creates a pressing need to understand what drives VA evaluations. This article proposes a new framework wherein perceptions of VA artificiality and VA intelligence are positioned as key drivers of VA evaluations. Building from work on signaling theory, AI, technology adoption, and voice technology, the authors conceptualize VA features as signals related to either artificiality or intelligence, which in turn affect VA evaluations. This study represents the first application of signaling theory when examining VA evaluations; also, it is the first work to position VA artificiality and intelligence (cf. other factors) as key drivers of VA evaluations. Further, the paper examines the role of several theory-driven and/ or practice-relevant moderators, relating to the effects of artificiality and intelligence on VA evaluations. The results of these investigations can help firms suitably design their VAs and suitably design segmentation strategies.
AB - Widespread, and growing, use of artificial intelligence (AI)–enabled voice assistants (VAs) creates a pressing need to understand what drives VA evaluations. This article proposes a new framework wherein perceptions of VA artificiality and VA intelligence are positioned as key drivers of VA evaluations. Building from work on signaling theory, AI, technology adoption, and voice technology, the authors conceptualize VA features as signals related to either artificiality or intelligence, which in turn affect VA evaluations. This study represents the first application of signaling theory when examining VA evaluations; also, it is the first work to position VA artificiality and intelligence (cf. other factors) as key drivers of VA evaluations. Further, the paper examines the role of several theory-driven and/ or practice-relevant moderators, relating to the effects of artificiality and intelligence on VA evaluations. The results of these investigations can help firms suitably design their VAs and suitably design segmentation strategies.
KW - 512 Business and Management
KW - Artificial intelligence
KW - Signaling
KW - Technology
KW - Voice assistants
UR - http://www.scopus.com/inward/record.url?scp=85133036062&partnerID=8YFLogxK
U2 - 10.1007/s11747-022-00874-7
DO - 10.1007/s11747-022-00874-7
M3 - Article
AN - SCOPUS:85133036062
SN - 0092-0703
JO - Journal of the Academy of Marketing Science
JF - Journal of the Academy of Marketing Science
ER -